Solving non-linear stochastic models by parameterizing expectations: An application to asset pricing with production

A new algorithm called the parameterized expectations approach(PEA) for solving dynamic stochastic models under rational expectationsis developed and its advantages and disadvantages are discussed. Thisalgorithm can, in principle, approximate the true equilibrium arbitrarilywell. Also, this algorithm works from the Euler equations, so that theequilibrium does not have to be cast in the form of a planner's problem.Monte--Carlo integration and the absence of grids on the state variables,cause the computation costs not to go up exponentially when the numberof state variables or the exogenous shocks in the economy increase. \\As an application we analyze an asset pricing model with endogenousproduction. We analyze its implications for time dependence of volatilityof stock returns and the term structure of interest rates. We argue thatthis model can generate hump--shaped term structures.

The optimal length of contracts with application to outsourcing

This paper resolves three empirical puzzles in outsourcing by formalizing the adaptationcost of long-term performance contracts. Side-trading with a new partner alongside a long-term contract (to exploit an adaptation-requiring investment) is usually less effective than switching to the new partner when the contract expires. So long-term contracts that prevent holdup of specific investments may induce holdup of adaptation investments. Contract length therefore trades of specific and adaptation investments. Length should increase with the importance and specificity of self-investments, and decrease with the importance of adaptation investments for which side-trading is ineffective. My general model also shows how optimal length falls with cross-investments and wasteful investments.

Hybrid consumption paths in the attribute space: A model and application with scanner data

This paper presents and estimates a dynamic choice model in the attribute space considering rational consumers. In light of the evidence of several state-dependence patterns, the standard attribute-based model is extended by considering a general utility function where pure inertia and pure variety-seeking behaviors can be explained in the model as particular linear cases. The dynamics of the model are fully characterized by standard dynamic programming techniques. The model presents a stationary consumption pattern that can be inertial, where the consumer only buys one product, or a variety-seeking one, where the consumer shifts among varied products.We run some simulations to analyze the consumption paths out of the steady state. Underthe hybrid utility assumption, the consumer behaves inertially among the unfamiliar brandsfor several periods, eventually switching to a variety-seeking behavior when the stationary levels are approached. An empirical analysis is run using scanner databases for three different product categories: fabric softener, saltine cracker, and catsup. Non-linear specifications provide the best fit of the data, as hybrid functional forms are found in all the product categories for most attributes and segments. These results reveal the statistical superiority of the non-linear structure and confirm the gradual trend to seek variety as the level of familiarity with the purchased items increases.

Improved estimation of the covariance matrix of stock returns with an application to portofolio selection

This paper proposes to estimate the covariance matrix of stock returnsby an optimally weighted average of two existing estimators: the samplecovariance matrix and single-index covariance matrix. This method isgenerally known as shrinkage, and it is standard in decision theory andin empirical Bayesian statistics. Our shrinkage estimator can be seenas a way to account for extra-market covariance without having to specifyan arbitrary multi-factor structure. For NYSE and AMEX stock returns from1972 to 1995, it can be used to select portfolios with significantly lowerout-of-sample variance than a set of existing estimators, includingmulti-factor models.

Forecasting with missing data: Application to a real case

This paper presents a comparative analysis of linear and mixed modelsfor short term forecasting of a real data series with a high percentage of missing data. Data are the series of significant wave heights registered at regular periods of three hours by a buoy placed in the Bay of Biscay.The series is interpolated with a linear predictor which minimizes theforecast mean square error. The linear models are seasonal ARIMA models and themixed models have a linear component and a non linear seasonal component.The non linear component is estimated by a non parametric regression of dataversus time. Short term forecasts, no more than two days ahead, are of interestbecause they can be used by the port authorities to notice the fleet.Several models are fitted and compared by their forecasting behavior.

Flexible multivariate GARCH modeling with an application to international stock markets

The goal of this paper is to estimate time-varying covariance matrices.Since the covariance matrix of financial returns is known to changethrough time and is an essential ingredient in risk measurement, portfolioselection, and tests of asset pricing models, this is a very importantproblem in practice. Our model of choice is the Diagonal-Vech version ofthe Multivariate GARCH(1,1) model. The problem is that the estimation ofthe general Diagonal-Vech model model is numerically infeasible indimensions higher than 5. The common approach is to estimate more restrictive models which are tractable but may not conform to the data. Our contributionis to propose an alternative estimation method that is numerically feasible,produces positive semi-definite conditional covariance matrices, and doesnot impose unrealistic a priori restrictions. We provide an empiricalapplication in the context of international stock markets, comparing thenew estimator to a number of existing ones.

Indentifying human capital externalities: Theory with an application to US cities

The identification of aggregate human capital externalities is still not fully understood. The existing (Mincerian) approach confounds positive externalities with wage changes due to a downward sloping demand curve for human capital. As a result, it yields positive externalities even when wages equal marginal social products. We propose an approach that identifies human capital externalities whether or not aggregate demand for human capital slopes downward. Another advantage of our approach is that it does not require estimates of the individual return to human capital. Applications to US cities and states between 1970 and 1990 yield no evidence of significant average -schooling externalities.

Grinder's Group Mastery Theory : scientific research and its application to classroom teaching

Estudi centrat en el paper de la comunicació no verbal com a eina docent per a la gestió de l’aula, prenent com a referència el model de comunicació de Michael Grinder (Pentimento), basat en la Programació Neuro-lingüística (PNL). Aquest model s’analitza i es compara amb altres models i estudis sobre la comunicació no verbal, per establir-ne similituds i diferències. Per tal d’avaluar l’eficàcia de les tècniques de gestió de l’aula a través de la comunicació no verbal proposades per Grinder en un context educatiu real, s’inclouen i s’analitzen enregistraments de la implementació de diferents tècniques en un institut de secundària de Catalunya. Tota la informació recollida i analitzada permet valorar i ressaltar com és de significatiu tot allò que s’expressa més enllà del llenguatge, i per tant, com són d’importants i d’útils les habilitats comunicatives d’un professor en la seva tasca d’ensenyar.

Characterization and Application of Educational Virtual Environments for Science Teaching in Secondary School

This work describes the characteristics of a representative set of seven different virtual laboratories (VLs) aimed for science teaching in secondary school. For this purpose, a 27-item evaluation model that facilitates the characterization of the VLs was prepared. The model takes into account the gaming features, the overall usability, and also the potential to induce scientific literacy. Five of the seven VLs were then tested with two larger and highly heterogenic groups of students, and in two different contexts – biotechnology and physics, respectively. It is described how the VLs were received by the students, taking into account both their motivation and their self-reported learning outcome. In some cases, students’ approach to work with the VLs was recorded digitally, and analyzed qualitatively. In general, the students enjoyed the VL activities, and claimed that they learned from them. Yet, more investigation is required to address the effectiveness of these tools for significant learning.

Application of a support system to the design of wastewater treatment plants

This paper presents a case study that explores the advantages that can be derived from the use of a design support system during the design of wastewater treatment plants (WWTP). With this objective in mind a simplified but plausible WWTP design case study has been generated with KBDS, a computer-based support system that maintains a historical record of the design process. The study shows how, by employing such a historical record, it is possible to: (1) rank different design proposals responding to a design problem; (2) study the influence of changing the weight of the arguments used in the selection of the most adequate proposal; (3) take advantage of keywords to assist the designer in the search of specific items within the historical records; (4) evaluate automatically thecompliance of alternative design proposals with respect to the design objectives; (5) verify the validity of previous decisions after the modification of the current constraints or specifications; (6) re-use the design records when upgrading an existing WWTP or when designing similar facilities; (7) generate documentation of the decision making process; and (8) associate a variety of documents as annotations to any component in the design history. The paper also shows one possible future role of design support systems as they outgrow their current reactive role as repositories of historical information and start to proactively support the generation of new knowledge during the design process

A methodology for the classification of convective structures using meteorological radar: Application to heavy rainfall events on the Mediterranean coast of the Iberian Peninsula

During the period 1996-2000, forty-three heavy rainfall events have been detected in the Internal Basins of Catalonia (Northeastern of Spain). Most of these events caused floods and serious damage. This high number leads to the need for a methodology to classify them, on the basis of their surface rainfall distribution, their internal organization and their physical features. The aim of this paper is to show a methodology to analyze systematically the convective structures responsible of those heavy rainfall events on the basis of the information supplied by the meteorological radar. The proposed methodology is as follows. Firstly, the rainfall intensity and the surface rainfall pattern are analyzed on the basis of the raingauge data. Secondly, the convective structures at the lowest level are identified and characterized by using a 2-D algorithm, and the convective cells are identified by using a 3-D procedure that looks for the reflectivity cores in every radar volume. Thirdly, the convective cells (3-D) are associated with the 2-D structures (convective rainfall areas). This methodology has been applied to the 43 heavy rainfall events using the meteorological radar located near Barcelona and the SAIH automatic raingauge network.

A press database on natural risks and its application in the study of floods in Northeastern Spain

The aim of this work is to introduce a systematic press database on natural hazards and climate change in Catalonia (NE of Spain) and to analyze its potential application to social-impact studies. For this reason, a review of the concepts of risk, hazard, vulnerability and social perception is also included. This database has been built for the period 1982¿2007 and contains all the news related with those issues published by the oldest still-active newspaper in Catalonia. Some parameters are registered for each article and for each event, including criteria that enable us to determine the importance accorded to it by the newspaper, and a compilation of information about it. This ACCESS data base allows each article to be classified on the basis of the seven defined topics and key words, as well as summary information about the format and structuring of the new itself, the social impact of the event and data about the magnitude or intensity of the event. The coverage given to this type of news has been assessed because of its influence on construction of the social perception of natural risk and climate change, and as a potential source of information about them. The treatment accorded by the press to different risks is also considered. More than 14 000 press articles have been classified. Results show that the largest number of news items for the period 1982¿2007 relates to forest fires and droughts, followed by floods and heavy rainfalls, although floods are the major risk in the region of study. Two flood events recorded in 2002 have been analyzed in order to show an example of the role of the press information as indicator of risk perception.